Dynamic creation and modification of wafer test maps during wafer testing

ABSTRACT

Methods, systems, and apparatuses provide dynamic creation and modification of wafer test maps. Test plans are defined for a testing session of a wafer lot. The test plan is associated with a number of seed map patterns. During a wafer lot testing session, test results are dynamically obtained and examined at run-time of a test. Moreover, the seed map patterns are overlaid on the test sites defined in the test plan. If the test result statistics are outside of defined threshold tolerance levels, then a new wafer test map is created or modified at run-time, according to corresponding seed map patterns. If seed map patterns are within the intersection of valid test sites, then seed map patterns are created at run-time.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of application Ser. No. 10/417,640, filed on Apr. 17, 2003, which is related to pending application Ser. No. 09/834,751, filed Apr. 13, 2001, titled “Concurrent Control of Semiconductor Parametric Testing,” which is incorporated herein by reference. The present invention is further related to pending application Ser. No. 10/131,934, filed on Apr. 25, 2002, titled “Intelligent Measurement Modular Semiconductor Parametric Test System,” which is incorporated herein by reference. The present invention is also further related to pending application Ser. No. 10/133,685, filed on Apr. 25, 2002, titled “Dynamically Adaptable Semiconductor Parametric Testing,” which is incorporated herein by reference.

FIELD OF THE INVENTION

The invention relates generally to testing semiconductors, and more specifically to dynamic creation and modification of wafer test maps during wafer testing.

BACKGROUND OF THE INVENTION

Fabrication of semiconductors typically comprises many steps, including creation of a silicon wafer, deposition of various materials onto the wafer, ion implantation into the wafer, etching away material applied to the wafer, and other similar processes. These processes are used to create the electronic components and connections on the wafer that form a useful electronic circuit.

As these processes are performed on the wafer, the wafer might be subjected to parametric testing. Parametric testing involves testing the electronic parameters of the circuitry on the wafer, such as by applying current or voltage, and by measuring resistance, capacitance, current, voltage, circuitry shapes, circuitry distances, or other such electrical parameters. These tests are used to ensure that a fabricated structure on the semiconductor meets the specifications and requirements of the semiconductor manufacturer and falls within acceptable tolerances.

Parametric testing can take place during the fabrication process to ensure that each stage of fabrication is successful, and is usually performed on the completed wafer to ensure that each completed circuit on the wafer is functional and meets specified performance criteria.

This parametric testing is typically performed with a parametric test system, which is comprised of several parts. Such systems might be capable of loading a wafer from a wafer tray to a wafer chuck, which is then properly alignment under a test pin by a wafer positioner. Once the equipment has properly loaded and positioned the wafer, parametric test instrumentation systems are initialized and operated to apply electrical signals, heat, and other stimuli as needed to the wafer. The test instrumentation also measures parameters, such as impedance and current or voltage measurement, and the test system then analyzes and records the results of the parametric tests.

Although parametric testing is typically used to verify the parameters or performance of production semiconductors, such testing can also be critical in investigating the usability or performance characteristics of new materials or new circuit structures. A wide variety of tests, including resistance, capacitance, transistor characteristic, thermal characteristic, and other tests enable characterization of these new materials and circuits, as well as verification of performance in a production environment.

Testing a single wafer can involve tens of thousands of measurements per wafer, with dozens of wafers per manufacturing lot or wafer tray loaded for test. Because this results in literally millions of parametric tests and measurements that must be performed per wafer lot, the time that such testing requires is an important factor in the productivity of a wafer or semiconductor fabrication facility.

Typically, testing is defined by test maps associated with predefined test plans that are developed by specialized staff, such as semiconductor engineers. Often, these engineers have a wealth of knowledge and experience that is not properly leveraged within an organization. Moreover, their knowledge and experience are often completely lost when engineers leave the organization.

Furthermore, predefined testing sessions are set aside for equipment access, which is required to test a wafer lot. If an engineer detects an area within a wafer that needs more thorough investigation during a testing session, then any additional tests that may be needed are delayed, developed, and processed during a different testing session, and the existing static tests are executed during the allotted testing session. This entire process is time consuming, static, and often unnecessarily duplicated.

For these reasons, there is a need to dynamically operate semiconductor parametric tests on wafers, thereby minimizing the use of development resources and processes during predefined testing sessions. Moreover, tests should be reusable and should enhance existing capabilities that verify performance characteristics of wafer structures under test.

SUMMARY OF THE INVENTION

Methods, Systems, and Apparatuses are provided for dynamic creation and modification of wafer test maps during a single test session. Wafer maps are dynamically created and modified based on initial developed test plans and by overlaying existing geometric patterns onto intersecting test sites, which are identified in the test plans, where test sites within new wafer maps are selectively or randomly chosen or both. The geometric patterns are associated with additional wafer maps. Moreover, wafer maps are created and modified upon parametric measurement values exceeding predefined thresholds or criteria during a testing session. As new wafer maps are developed and associated with geometric patterns, the geometric patterns and concomitant wafer maps are stored in a data repository for future use during other testing sessions.

BRIEF DESCRIPTION OF THE FIGS.

FIG. 1A depicts a block diagram of the components of a dynamic wafer test system, according to one embodiment of the present invention.

FIG. 1B depicts a block diagram of component detailed view for a wafer test system, according to one embodiment of the present invention.

FIG. 2 depicts a sequential run time diagram for newly created prober 106 movement patterns during lot run-time (e.g., testing session), according to one embodiment of the present invention.

FIG. 3A depicts a diagram representing example wafer test sites that are associated with a wafer test plan, according to one embodiment of the present invention.

FIG. 3B depicts a diagram representing an example and an initial wafer test map pattern associated with example wafer test sites of FIG. 3A, according to one embodiment of the present invention.

FIG. 3C depicts a diagram representing an example for a dynamically created wafer test map pattern associated with the example test sites of FIG. 3A and selected during the testing of the initial wafer test map pattern of FIG. 3B, according to one embodiment of the present invention.

FIG. 4 depicts a pictorial diagram for example dimensions and conditions, which are dynamically identified in a test plan associated with FIG. 3A during testing of the initial wafer test map pattern of FIG. 3B in order to create the wafer test map pattern of FIG. 3C, according to one embodiment of the present invention.

FIGS. 5A-5D depict pictorial diagrams of differently shaped templates and their dimensions and conditions derived from and processing performed on test sites of FIG. 3A in order to dynamically create the wafer test map similar to the one depicted in FIG. 3C and associated with various geometrical patterns of interest, according to one embodiment of the present invention.

FIGS. 6A-6F depict various diagrams for example filters and hardware architecture configurations controlling triggering the creation of new maps, according to various embodiments of the present invention.

FIG. 7A-71 depict various class and object diagrams and state charts for processing and software architecture configurations involved in new map creation, according to various embodiments of the present invention.

DETAILED DESCRIPTION

In the following detailed description of sample embodiments of the invention, reference is made to the accompanying drawings which form a part hereof, and in which is shown by way of illustration specific sample embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those of ordinary skill in the art to practice the invention, and it is to be understood that other embodiments may be utilized and that logical, mechanical, electrical, and other changes may be made without departing from the spirit or scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the invention is defined only by the appended claims.

FIG. 1A illustrates a dynamic wafer test system 100, according to one embodiment of the present invention. A parametric test system 100 includes a test station 101 connected to an integrated prober 102, which provides wafer movement capability. The integrated prober comprises a wafer loader 103, an auto-alignment system 104 for aligning wafers, an Optical Character Recognition (OCR) system 105, and a prober 106. The prober 106 comprises test pins, as well as a wafer chuck and mover system (not shown in FIG. 1A) that coordinates with the auto-alignment system 104.

The test station 101 is also connected to an integrated measurement system 107, which includes a capacitance meter 108, a digital multimeter (DMM) 109, and a parametric measurement system 110, which are operable to perform measurements and tests.

The test station 101 is also interfaced to test files 111, which store parameters for the wafer under test. These parameters include definitions of the test to be performed on the wafer and of the data to be collected during the wafer tests. Parametric (PARM) data store 112 houses information including the results of the tests, as well as statistics summarizing the test results.

A dynamic wafer test system 100 illustrated in FIG. 1A demonstrates how test instrumentation for one embodiment of the present invention uses an integrated measurement system 107 and an integrated prober system 102. These systems 102 and 107 can be integrated with each other in configurations that are not depicted in FIG. 1A. For example, a wafer chuck of the prober 106 can be heated or cooled by the integrated measurement system 107 or another part of the wafer test system 100. The operation of these various systems is controlled and coordinated by a test station controller 101.

The test station controller 101 can read maps from the test files 111, perform the tests specified in maps on a wafer via the integrated measurement system 107 and integrated prober 102, receive the results of the tests from the integrated measurement system 107, and can record the results in the PARM data store 112. The test station controller 101 includes instructions that are accessible to a machine-readable medium and capable of being executed on a processor. Furthermore, in some embodiments, the test station controller 101 can be implemented in hardware/firmware. The functions of the test station controller 101 can be distributed in the integrated measurement system 107 and/or the integrated prober 102. The functions of the test station controller 101 can also include any control functions of the integrated measurement system 107 and/or the integrated prober 102.

In one embodiment, a Parametric Probe Card Tracking Interface to a Probe Card Tracking System can also be integrated into system 100 in order to reduce probe card costs by optimizing scheduled maintenance of needle cleaning.

FIG. 1B illustrates a more detailed view of FIG. 1A that depicts additional components and sub-components of dynamic wafer test system 100, according to one embodiment of the present invention. Moreover, FIG. 1B also depicts various information passing between components of system 100, and logical sub-components of system 100. FIG. 1B is provided as one example configuration for one embodiment for dynamic wafer test system 100 associated with the present invention. Various other configurations of the depicted components can be added, removed, and/or arranged differently. All such permutations are intended to fall within the scope of the present invention.

As shown in FIG. 1B, the test station controller 101 includes an operator interface 101A, a fabrication wafer lot tracking client 101B, a probe card tracking client 101C, a concurrent-multiple wafer inline engine control server (CWE) 101D, an intelligent measurement module 101E, a test monitoring server 101F, a plug-in test module 101G, a test specification server 101H, a test result server 101I, a prober monitor server 101J, and a plug-in prober module 101K.

The CWE 101D dynamically creates new wafer test maps during a lot testing session. Further, the CWE 101D interacts and drives the processing of wafer testing during lot test sessions as a subcomponent module of the test station controller 101. Thus, the CWE 101D acquires a test plan for a wafer lot test session using its test specification server 101H interface in order to load the test plan from a test files data store 111. An operator (e.g., semiconductor engineer) determines a specific test plan to load using the operator interface 101A to interact with the test station controller 101.

The integrated prober system 102 uses its wafer loader 103, automatic alignment 104, OCR 105, wafer chuck 106A, and prober card 106B to acquire an initial wafer under test, manipulate the wafer, and perform operations on the wafer. The prober 106 includes a wafer chuck moving system 106A capable of moving wafers left (X), right (Y), and vertically (Z) within the prober 106.

The CWE 101D communicates acquisition and placement of wafers being tested to the integrated prober system 102 through its prober monitor server 101J. Moreover, confirmation of successful contact or touchdown for a loaded wafer is communicated back to the CWE 101D through the prober monitor server 101J interface. In some embodiments, one or more lower level interfaces (e.g., device drivers) associated with the integrated prober system 102 act as intermediate interfaces between the CWE 101D and the integrated prober system 102 (e.g., plug-in prober module 101K). The integrated prober system 102 then loads, aligns, and scans the wafer being tested, and performs wafer movements according to the test sites and sub site locations specified in the test plans (or maps), requested by the CWE 101D.

Test plans include a number of test locations or wafer sites that are to be testing on wafers in system 100. Moreover, the test plans can include one or more predefined wafer test maps to initially test on the wafer lots. The CWE 101D communicates the sites and desired test operations, identified in the test map of the test plan, to the integrated measurement system 107 through a test monitor server 101F interface. In turn, one or more lower level plug-in interfaces (e.g., device drivers, such as plug-in test module 101G) translate the CWE 101D commands to drive test operations/commands recognized by the integrated measurement system 107.

The integrated measurement system 107 uses its components during a test in order to communicate specific types of test operations for specific wafer sites. The test operations and wafer sites are communicated initially from the CWE 101D through the test monitor server 101F interface and the plug-in test module 101G interfaces. The integrated measurement system 107 performs test operations by applying the tests to the wafer site via the prober 106. Measurements and results acquired by the components of the integrated measurement system 107 are sent back to the CWE 101D through the plug-in test module 101G interfaces and the test monitor server 101F interfaces. Measurements and results are then placed in the intelligent measurement module 101E.

Upon receiving measurement results, the intelligent measurement module 101E dynamically compares the results against predefined threshold values. The results are also recorded in the PARM data store 112 through the test result server 101I interface. If results fall outside a defined tolerance for the threshold values, then the CWE 101D is triggered and can dynamically alter, suspend, and/or initiate a newly created wafer test map using test plans and seeds from the test files data store 111, or any other computer-accessible media. Furthermore, the CWE 101D can inspect the wafer test sites identified in a test plan before or during a lot testing session and overlay a number of predefined geometric patterns on the test sites. The intersection of test sites with a geometric pattern indicates that additional wafer test maps can be created and used during the lot testing session.

Thus, as experienced semiconductor engineers identify geometric patterns associated with previously developed wafer test maps, these maps can be maintained in the test files data store 111, or in any other computer-accessible media. Correspondingly, during any particular lot testing session, the CWE 101D can be configured (e.g., before, during, or after) to evaluate geometric patterns against test sites. If matches occur, newly created wafer test maps are instantiated and communicated appropriately to the integrated measurement system 107, and to the integrated prober 102.

Furthermore, the geometric patterns and the measurement results need not be mutually exclusive conditions with respect to altering, suspending, or creating wafer test maps. In other words, the CWE 101D can be configured to instantiate a newly created or altered wafer test map based on matches (or substantial matches) with geometric patterns and/or based on specific results that are outside a predefined threshold tolerance.

Accordingly, with various embodiments of test system 100, wafer test maps can be dynamically created and/or modified during a given lot testing session. Therefore, the experience of a semiconductor engineer is leveraged, maintained, dynamically acquired, and used when appropriate during a lot testing session through the acquisition and reuse of the wafer test maps, thereby creating an engineering knowledge data store/bank. In this way, wafer testing dynamically proceeds during an allocated lot testing session with more complete, accurate, and efficient tests. Moreover, repetitive tests are avoided, and manual recreation of previous test maps is circumscribed.

In various embodiments, test system 100 also includes additional components, such as a manufacturing execution server 113 that provides monitoring, inventory control, and/or tracking of wafers and/or wafer lots being tested. The CWE 101D interfaces with the manufacturing execution server 113 through the fabrication lot tracking client 101B. Furthermore, inventory control and tracking information can be recorded or replicated in a probe card database 117.

Additionally, in other embodiments, test system 100 includes a probe card tracking server 116 to maintain and support various aspects of the prober cards 106B. The CWE 101D interfaces to the probe card tracking server 116 through its probe card tracking client 101C. Information regarding this tracking, support, maintenance, and the like is also captured and stored in the probe card database 117.

An operator/engineer can interface and direct various reports for purposes of data mining, maintenance, and support of the overall test system 100 through a number of interface applications, such as web-based user interface 115. In turn, for purposes of efficiency and response time, a cache 114 can be used between the user interface 115 and the probe card database 117.

FIG. 2 illustrates a diagram 200 of newly created prober 106 movement patterns during lot run-time (e.g., lot testing session), according to one embodiment of the present invention. The prober 106 movement patterns are being dynamically created and instantiated or acquired during the lot testing session, as directed by the test station controller 101. Thus, dynamically created and modified strategic wafer test maps/patterns can be acquired and used to drive the prober 106 movements at lot run-time based on a statistical threshold or other criteria that is not necessarily statistical (e.g., based on business rules or fuzzy logic).

At run-time, a wafer test map is created or modified that can include a new series of test locations/sites on a wafer. This new series of test locations can be obtained from the actual absolute site locations that represent the entire site population specified in the test plan. The newly created wafer map/pattern determines what electrical tests are to execute and where on the wafer the electrical tests are to execute.

For each fabrication facility, there is a limited number of parametric test systems and a limited number of semiconductor experts. In various embodiments of the present invention, a new map/pattern is created at lot run-time the same way the semiconductor engineer, who is cognizant of the part-type specific production issues, would create a unique wafer test map strategy off-line after examining the test results of the wafer lot that had run previously on the parametric test system. Conventionally, the time to re-probe a wafer lot placed on hold takes at least 20 minutes during a testing session and that time is wasted. For example, when an engineer is notified by the parametric inline test system of a problem, the engineer proceeds to prescribe a new wafer test map for a wafer lot on hold. An operator then loads the wafer lot onto the test system and proceeds to re-test. To ensure maximum throughput per parametric test system, this invention, with various described embodiments, makes the most efficient use of allocated test time for each lot under test.

The dynamic creation of a wafer test map occurs while a wafer is still on the test platform, saving time and engineering resources. In other words, the semiconductor engineer does not have to wait for the wafers to finish testing, and avoids re-testing by using a preferred geometric shape to dynamically identify and load any needed wafer test map.

Various embodiments of the present invention seed the dynamic map creation with a preferred geometric shape instantiated from a bank (e.g., a data or knowledge store) of seeds that are sensitive to previous failing site location symptoms for a given part-type and manufacturing step.

The semiconductor engineer, who has a vested interest in the success of the part-type, can select seeds off-line using the test station controller 101 to access the test files data store 111. The seeds are associated with specific test registers.

Examples of seed maps that can be associated with a register include: Single-Site, Center-To-Edge, Edge-Only, Center-Only, Notch-Only, All Testable Sites, Donut and Hourglass, and so on, which are depicted further in FIG. 4 and FIGS. 5A-5D. The actual sites that can be tested are not pre-specified in the test plans stored in the test files 111 and used later by the test station controller 101. Instead, the seed map is used at run-time to form a dynamic wafer test map pattern. Therefore, the new wafer test map pattern is always a subset of valid test sites on the wafer. For example, consider Table 1 that identifies upstream manufacturing process problems related to finding problem geometric shapes: TABLE 1 Upstream Process Problems Detected Shape that Finds Problem or by Inline Parametric Testing would Test Out the Problem Over Etched, Under Etched Donut, Edge-to-Center, Notch-Only, or Half-Moon Implant Problem or Incorrectly Processed Single-Site Diffusion Furnace Processes, including All Testable Sites, Edge-Only, Poly, Gate Oxide, or Nitride Deposition Center-To-Edge E-Field or Plasma Processes Half Moon, Hourglass Photolithography or Etch Process Edge-Only Combination Residual Poly Feet Notch-To-Center BPSG Deposition Center-Only 300 mm Other Seeded Wafer Map Patterns . . .

By way of example only, in Table 1, if a lot misses an implant, some of the parametrics may read out of specification at all test locations. Since this can affect the entire wafer fabrication, and testing processes, an engineer wants to determine how many wafers are affected. Thus, all subsequently tested wafers may be tested with a SINGLE-SITE created wafer test map. This can save hours of test and engineering time.

In another example, an engineer might want to determine the effect of an under-etch problem occurring throughout the wafer lot. The engineer may already know that an under-etch problem can propagate from an edge toward a center of the wafer. Accordingly, if a wafer being tested has edge fails, an EDGE-ONLY wafer test map can be created to further investigate the scope of the problem.

Embodiments of the present invention enable wafer test map/patterns to be created dynamically at run-time, which enables semiconductor engineers to better understand upstream manufacturing process problems associated with a particular part-type.

With this background, one can visualize in diagram 200 of FIG. 2 how prober 106 movement patterns or maps are dynamically changed to conduct tests on newly instantiated, created or modified wafer test maps 203-206 during a testing session. Initially, a test plan is used to perform an initial wafer test map 201, at some time thereafter at least some of the second test map can be partially tested 202. In other embodiments, any newly created wafer test maps 203-206 can be delayed until after the initial test maps 201 and 202 completes on the first wafer in the wafer lot.

Thereafter, based on pre-selected seeds associated with the test plan, geometric patterns associated with existing seeds and/or measurement results obtained from a partial test of the second wafer test map 202 are evaluated to dynamically instantiate a number of newly created wafer test maps 203-206. The prober 106 is then instructed to dynamically change patterns or maps and perform tests on test sites defined in the newly created wafer test maps. Finally, in some embodiments, a single composite wafer test map 206 can be generated based on a number of the created wafer test maps 204-205. This composite wafer test map 206 (as well as 203, 204, or 205) can be reused with other lot tests or used for remaining wafers being tested in the wafer lot during a testing session.

FIG. 3A illustrates diagram 300A depicting all possible example test sites on a wafer that are associated with a wafer test plan, according to one embodiment of the present invention.

In order to create new wafer test map/pattern at run-time, all testable sites are defined prior to executing a test. FIG. 3A shows an example site definition for a particular wafer part defined by using a test plan created using sub-modules of the operator interface 101A (or any other editor interface separate and distinct from the operator interface 101A). All site locations 301A are defined in the test plan in order to properly create valid wafer test map patterns that resolve to physical test structures located between dies.

All of the shaded squares of FIG. 3A represent the test sites 301A defined in the test plan for the wafer part under test. A specific selected site for test is identified as 302A, a setup die site is identified as 303, and a reference die site is identified as 303.

FIG. 3B illustrates a diagram 300B of an example and initial wafer test map pattern associated with a test plan that is to be tested, according to one embodiment of the present invention. Specific test sites that are to be examined, according to the wafer test map pattern, are identified as 303B and currently selected site in the wafer test map pattern is identified as 301B.

FIG. 3C illustrates a diagram 300C of an example wafer test map pattern, which is dynamically selected and created during testing of the initial wafer test map pattern identified in FIG. 3B, according to one embodiment of the present invention. Specific test sites that are dynamically determined for examination are identified as 303C, and currently selected site in the wafer test map pattern is identified as 302C. It should be noted that the setup and reference dies may be included in test sites determined for testing.

Conventionally, in order for a semiconductor engineer to shift testing from the initial wafer test map pattern of FIG. 3B to the new wafer test map pattern of FIG. 3C, the engineer would have to perform a number of data store lookups to evaluate parametric lot data that was put on hold in order to run the initial wafer test map pattern of FIG. 3B. It may take the engineer 10 to 15 minutes to complete this evaluation and determine that the wafer test map pattern of FIG. 3C should be used, instead of the initial wafer test map pattern of FIG. 3B. Additionally, the re-probe needed to test the desired wafer test map pattern of FIG. 3C needs to occur during separate wafer lot runs. Running the reprobe wafer test map pattern can require at least another 5 minutes of engineering interaction to set up a second lot run.

Conversely, in various embodiments of the present invention, the wafer test map pattern in FIG. 3C is dynamically created during the lot run, and the initial wafer test map pattern in FIG. 3B is abandoned. Moreover, the wafer test map pattern in FIG. 3C, is a good candidate pattern to be used at run-time when a statistical threshold is exceeded.

The phrase “candidate pattern” indicates that a general area of a re-probe geometric shape is overlaid on the existing site population specified in FIG. 3A. Prior to creating the wafer test map pattern in FIG. 3C, actual site locations associated with the map have not yet been determined. All untested sites or a percentage/random sample of untested sites that fall within boundaries of the new test pattern can be included in the resultant created wafer test map pattern of FIG. 3C. A favorite seed map pattern is selected upon evaluating criteria specified in the test plan. More specifically, a seed map pattern is associated with a test register. Each test register uniquely identifies a kind of parametric measurement.

FIG. 4 illustrates a diagram 400 for example dimensions and conditions, which are dynamically identified in a test plan associated with FIG. 3A during testing of the initial wafer test map pattern of FIG. 3B, according to one embodiment of the present invention. The identified dimensions are used to dynamically create the wafer test map pattern in FIG. 3C. All possible test sites that reside inside the specified wafer boundary are specified in the test plan of FIG. 3A.

Moreover, a seed bank data store contains one or more selectable geometric and/or trigonometric definitions based on one or more shape templates. For example, FIG. 4 illustrates dimensions discovered from the wafer test plan used in FIG. 3A, while testing is occurring on the wafer test pattern of FIG. 4. This is done by using shape templates having formal mathematical representations for defined shapes to identify new wafer test map patterns. Shape templates can be automatically identified with unique file names or record identifiers. In one example, a specific shape template dimensions are in a file identified by the name “T9_(—)52_A.wtp.” The ‘A’ in file T95_(—)52_A indicates that this file defines all test sites for a given wafer test map pattern associated with test plan of FIG. 3A. Any additional desired wafer test map patterns can be identified with another template, and the additional template includes a formal representation used to determine the sites for the additionally created wafer test map pattern.

FIG. 4 illustrates a pictorial diagram 400 of a geometric pattern identified from test sites of FIG. 3A, according to one embodiment of the present invention. FIG. 4 is presented for purposes of illustration only. The geometric pattern of diagram 400 corresponds to the newly created map of FIG. 3C. The geometric pattern is derived by overlaying a shape template on the test sites of FIG. 3A. The example shape template dimensions can be formally defined within the file T95_(—)52_A as: [setup] fileName = T95_52_A.wtp version = 12 DesignID = T95 [mapSetup] origin = TR // Top Right units = M // Metric waferDiameter = 200 // 200 mm = 8″ DieSize = 7604, 7127 // Die Size in Microns NoCols = 25 NoRows = 27 ReticleFrameSize = 3, 2 // Reticle Frame size in die ReticleShift = −4, −3 // Reticle Shift flat = L // Notch position SetupDie = 15, 2 ReferenceDie = 10, 2

Coordinates x₀, y₀ define the center of the wafer and d is the wafer diameter. Since dies are different sizes from part to part, the photolithography determines the maximum number of die per wafer. An engineer cannot depend on there being an intersection at the center of the wafer and cannot depend on a reticle field being in the center of the wafer. Therefore, the x reticleshift and y reticleshift compensates for various part-type layouts. The reticle offset will not shift once the part starts production in the wafer testing environment. $x_{0} = {\frac{d}{2} - {x\quad\text{reticle~~shift}}}$ $y_{0} = {\frac{d}{2} - {y\quad\text{reticle~~shift}}}$

Let Map, M, be a set of test sites in the total test plan population as illustrated by FIG. 4, Area, A, is the set of all sites included in the donut area, and EM is the excluded set of sites that are not elements of any of the sites in the included set A. M:set={S₁,S₂, . . . ,S_(m)} A:set={S_(i1), S_(i2), . . . ,S_(ia)} EM:set={{S_(e1) ∉ A,S_(e2) ∉ A, . . . ,S_(em) ∉ A} ⊂ M}

Radius R_(i):R is the distance between the center of the wafer and a test site in the test plan 400A and this radius can identify one or more sites in set A: R _(i)=√{square root over ((x ₀ −x _(i))²+(y ₀ −y _(i))²)}

Radius R_(e):R is the distance between the center of the wafer and the outer edge of the exclusion area 400B and where this radius identifies each site in the excluded set EM: $R_{e} = {\left( \text{percent} \right)\frac{WaferDiameter}{2}}$

For quantification 400C, there exists a site, S<x_(i),y_(i)>, such that S<x_(i),y_(i)> is an element of set, A, that intersects set M, qualified by predicate, included. The predicate, included, evaluates to true if the wafer radius lower bound, R is greater than the radius being tested, R_(i), and, R_(i), is greater than the excluded radius upper bound, R_(e). ∃S<x _(i) ,y _(i)>|(S<x _(i) ,y _(i) >ε A∩S<x _(i) ,y _(i) >ε M):included(R>R _(i) >R _(e)) Therefore, set area, A, is the difference between set M and set EM: :.A:set=M:set−EM:set

At run-time, if a threshold is exceeded on a register (e.g., upper control limit), iterating over all sites in set, M, the subset of sites that are included in the requested donut area, set A can be found: A:set ⊂ {∀S<x _(i) ,y _(i) >⊂ M|(R>R _(i) >R _(e))→S ε A}

FIGS. 5A-5D illustrate pictorial diagrams for different shape templates and their dimensions and conditions derived from and processed on the test sites of FIG. 3A in order to dynamically create the wafer test map similar to the one of FIG. 3C, according to one embodiment of the present invention.

FIG. 5A illustrates reversing donut sites in a region of interest for creating the wafer test map pattern similar to the one of FIG. 3C and can be formally represented as: ∃S<x _(i) ,y _(i)>|(S<x _(i) ,y _(i) >ε A ∩ S<x _(i) ,y _(i) >ε M):included(R_(i) ≦R _(e))

FIG. 5B illustrates nesting donut sites in regions of interest for hatching the wafer test map pattern of FIG. 3C, and can be formally represented as: ∃S<x _(i) ,y _(i)>|(S<x _(i) ,y _(i) >ε A∩S<x _(i) ,y _(i) >ε M):included((R_(ei) <R _(i) <R)v(R _(i) <R _(e2)))

FIG. 5C illustrates finding edge sites to test an over-etched region. A test plan specifies constants, R₂ and d₂. Where R₂ is the percentage of the radius associated with the Right Round Shape. And, where d₂ is the distance between two overlapping round shapes. $\begin{matrix} {R_{2} = {\left( \text{percent} \right)\frac{WaferDiameter}{2}}} \\ {d_{2} \leq {WaferDiameter}} \\ {d_{1} > {WaferRadius}} \end{matrix}$

Alternatively, the coordinates such as X_(A), Y_(A) may be transformed into polar coordinates calculated from angle α. Y_(A)=d₁●sin α X_(A)=d₁●cos α

Let M be a set of test sites in the total population, area, A, is the included set of all sites included in the moon-like pattern, and EM is the excluded set of sites that are not elements of any of the sites in set A and subset of set M. M:set={S₁,S₂, . . . ,S_(m)} A:set={S₁,S₂, . . . ,S_(a)} EM:set={{S_(e1) ∉ A,S_(e2) ∉ AREA, . . . ,S_(em) ∉ A} ⊂ M} Let |CB| be the distance between two points on the Right Round shape: |CB|≡√{square root over ((X_(C)−X_(B))²+(Y_(C)−Y_(B))²)} Let |CA| be the distance between two points on the Left Round shape: |CA|≡√{square root over ((X_(C)−X_(A))^(2 +(Y) _(C)−Y_(A))²)}

|CA| distance ˆ|CB| distance identifies one or more sites in the set area, A, (e.g., Edge Test Region) only if |CA|<R₁ˆ|CB|<R₂ evaluate to true. There exists a site, S<x_(c),y_(c)> such that this site is an element of the set area, A, that is a subset of the set M only if the predicate, included evaluates to true: ∃S<x _(c) ,y _(c)>|(S ε A ∩ S ε M):included((|CA|<R ₁)ˆ(|CB|<R ₂)) At run-time iterating over all sites in the set M we find the A subset: A:set ⊂ {∀S<x _(i) ,y _(i) >⊂ M|included((|CA|<R ₁)ˆ(|CB|<R ₂)→S<x _(i) ,y _(i) >ε A}

Building on previous examples, FIGS. 5A-5C and FIG. 5D show how the test plan can specify two half moon shapes resulting in finding sites located in the outer edges of the wafer under test. Thus, FIG. 5D may show a search processing at run-time for an unknown 300 mm problem that needs an hourglass test pattern or symmetrical edge test pattern.

FIG. 6A illustrates a pictorial diagram 600A of one example Finite Impulse Filter (FIR) used to suppress the unnecessary triggering creation of new wafer test maps during a lot testing session, according to one embodiment of the present invention.

To induce wafer map creation during a lot testing session, there are N dedicated In Situ Statistics Sensors (ISSS)—by—M dedicated In Situ Statistics Processors (ISSP). Each ISSS is driven by a measurement acquired from the integrated measurement system 107 and a register uniquely identifies each kind of measurement.

After each measurement acquisition, the measured result is rendered on or by graphical user interface (GUI). Concurrently, while the measurement is being rendered, the dedicated ISSP processor associated with that kind of measurement calculates the statistics. Each ISSS sensor can sense more than one type of statistic, such as: mean, standard deviation, sum, median, IQR, minimum, maximum, percent fail, percent short, and percent range. FIG. 6B illustrates an example machine architecture 600B for a processor, including a filter bank and a sensor bank for each test register. Each ISSS sensor's resulting statistic is latched and then evaluated against an upper control or lower control limit specified by the type of statistic. If a limit is exceeded, then the ISSS sensor notifies the multithreaded parametric inline engine control. In response to the notification (event stimulus), the seed associated with the register is used to create shape boundary over the intersecting sites, as illustrated by FIG. 4 and FIGS. 5A-5D. This area subset instantiates the wafer test map that is invoked and it is this wafer test map that can govern the movement progression of the prober subsystem on the next pass.

Suppressing a wafer test map creation can yield more test time for the hundreds (or thousands) of other sensors, which can also reach their control limits. Therefore it is desirable to avoid noisy ISSS triggering of the parametric inline engine control to create a new wafer test map. In a worst-case scenario, wafer test maps may continuously be created until all test sites have been tested.

Thus, to prevent noisy triggering, a suppression filter can be applied to statistic data ISSS. In some embodiments, there are two candidate filters: FIR depicted in FIG. 6A and Infinite Impulse Response (IIR) filters. FIRs are good candidates for band filters. FIR examples include Chebyshev, Butterworth, and Battler filters.

Given statistics input, x_(j), the discrete FIR function response (FIG. 6A) produces output, y_(i): $y_{i} = {\sum\limits_{j = 0}^{n}\quad{w_{j} \times x_{t - j}}}$

Where n is the number of statistic data samples back in time posted by the ISSP, and w_(j) are weighting factors of the filter that determine its type and characteristics. Notice the following precondition exits for the discrete FIR. ${\sum\limits_{j = 0}^{n}\quad w_{j}} = 1$

FIGS. 6C and 6D show example possible input signal shapes and FIR Filter responses.

In contrast, IIRs can be good candidates for unknown noisy signals. For the initial, testing environments, prototypes, and in some embodiments, an engineer can select dedicated IIR filtering on each ISSS. FIG. 6E illustrates a block diagram 600E describing the essential input/output relationship of an IIR filter, which can be applied to each ISSS. For example, an Exponentially Weighted Moving Average (EWMA) filter can be the fastest one.

Thus, given statistics input, x_(j), the IIR function response produces output, y_(i): y _(i) =αx _(i)+(1−α)y _(i-1)

In implementation, the IIR Filter class can store the constant α (e.g., 0.5). The expression, y_(i-1), is a previous filter output. The previous filter output persists in the class instance. Therefore, x_(i) is the input statistic and y_(i) is the filtered output statistic. The IIR response is shown below in FIG. 6F.

The initial first sample may use condition that y_(i-1)=x_(i) as no previous output is known at the first sample. Notice in FIG. 6F that α₁, α₂, and a₃ denote settling time to 95 percent of impulse input signal with a logical high reduced to 95 percent. α₁>α₂>α₃

If α=1, then there is no filtering: α=1→UNITY

With various kinds of measurements (e.g., 32,000 types of measurements per test), there is a dedicated ISSP, IIR Filter Bank, and ISSS for each register (FIG. 6B). The sensor would trigger the creation of a new wafer test map.

The various embodiments of configurations and filters depicted in FIGS. 6A-6F can be implemented in hardware, software, and/or a combination of software and hardware. In a hardware implementation, in some embodiments, Re-programmable Field Programmable Gate Arrays (FPGAs) is used so that the machine architecture 600B of FIG. 6B is achieved.

Notice in FIG. 6B, each acquired measurement is buffered in Random Access Memory (RAM) and processed by its own dedicated processor, filter, and sensor. Each sensor compares the data statistic to the upper statistic limit and lower statistic limit. This can be done using a window comparator circuitry. If either limit is exceeded, then corresponding output of the sensor may be latched.

In various embodiments of the present invention, the following keywords specify what kind of statistics can be performed on a register depicted in example machine architecture in FIG. 6B. These keywords follow the register specification in a test plan and represent the statistics that are performed on each particular register. Kind of Statistic Semantics Fail Specifies that a percentage of all failures to be performed. A state of failure is determined by the fact that the register value is greater than or equal to Upper Acceptable Value (UAV) or lower than or equal to Lower Acceptable Value (LAV) or equal to 998.0. A hold condition will be flagged if the percentage of failures is less than or equal to Lower Hold Limit (LHL) or greater than or equal to Upper Hold Limit (UHL). For example: fail = .01, 10, ,5 Open Specifies that a percentage of all-opens to be performed. A state of open is determined by the fact that the register value is greater than or equal to UAV. A hold condition will be flagged if the percentage of opens is less than or equal to LHL or greater than or equal to UHL. For example: open = , 100.0, 10, 80 Short Specifies that a percentage of all shorts to be performed. A state of short is determined by the fact that the register value is less than or equal to LAV. A hold condition will be flagged if the percentage of opens is less than or equal to LHL or greater than or equal to UHL. For example: short = 100.0, , 10, 80 Range Specifies that a percentage of all values in the specified range to be performed. A state of falling in the specified range is determined by the fact that the register value is between LAV and UAV. A hold condition will be flagged if the final calculation is outside of the LHL and UHL or equal to them. For example: range = , 3.6, 4.6. Mean Specifies that a mean calculation will be done on the data. The calculation excludes all values of 998.0, 999.0, and −999.0. The data is included in the calculation if it is between LAV and UAV. A hold condition will be flagged if the final calculation is outside of the LHL and UHL limits or equal to them. For example: mean = , 3.6, 4.6, 1223 Median Specifies that a median calculation will be done on the data. The calculation excludes all values of 998.0, 999.0, and −999.0. The data is included in the calculation if it is between LAV and UAV. A hold condition will be flagged if the final calculation is outside of the LHL and UHL limits or equal to them. For example: median = , 200.0, 100.0, 1000, 435 StandardDeviation Specifies that a standard deviation calculation will be done on the data. The calculation excludes all values of 998.0, 999.0, and −999.0. The data is included in the calculation if it is between LAV and UAV. A hold condition will be flagged if the final calculation is outside of the LHL and UHL limits or equal to them. For example: stddev = , 125.8, , 20.0 Total Specifies that a total calculation will be done on the data. The calculation excludes all values of 998.0, 999.0, and −999.0. The data is included in the calculation if it is between LAV and UAV. A hold condition will be flagged if the final calculation is outside of the LHL and UHL limits or equal to them. For example: total = , , , , IQR Specifies that a Inter Quartile Range (IQR) calculation will be done on the data. The calculation excludes all values of 998.0, 999.0, and −999.0. The data is included in the calculation if it is between LAV and UAV. A hold condition will be flagged if the final calculation is outside of the LHL and UHL limits or equal to them. For example: iqr = , , 100, 200 Min Specifies that a minimum calculation will be done on the data. The calculation excludes all values of 998.0, 999.0, and −999.0. The data is included in the calculation if it is between LAV and UAV. A hold condition will be flagged if the final calculation is outside of the LHL and UHL limits or equal to them. For example: min = , 100, , 50 Max Specifies that a maximum calculation will be done on the data. The calculation excludes all values of 998.0, 999.0, and −999.0. The data is included in the calculation if it is between LAV and UAV. A hold condition will be flagged if the final calculation is outside of the LHL and UHL limits or equal to them. For example: max = 100, , , 200

Additionally, in some embodiments, the following keywords are the parameters used to define each kind of statistics for a register: Statistical Parameters Per Register Semantics LAV Lower Acceptable Value. Determines the lower range for a register value to be included into statistic calculations. Default value = −1.0e30. UAV Upper Acceptable Value. Determines the upper range for a register value to be included into statistic calculations. Default value is +1.0e30. LHL Lower Hold Limit. Determines the smallest acceptable statistic value (or percentage for fail, open, short, range) that can be encountered without flagging a hold condition. Hold condition will be flagged if statistic is less than the limit. Default value is −1.0e30. UHL Upper Hold Limit. Determines the greatest acceptable statistic value (or percentage for fail, open, short, range) that can be encountered without flagging a hold condition. Hold condition will be flagged if statistic is greater than the limit. Default value is +1.0e30. LT Lot Tracking register number specifies if the lot tracking is supported. The executive will generate the track files (*.TRK) and include statistics with specified LT number. This file will later be sent to the lot-tracking database. Lot tracking is available for all statistics. Lot tracking register number is optional. IIR FILTER To drive the Infinite Impulse Response EWMA COEFFICIENT Filter, y_(i) = ax_(i) + (1 − a)y_(i−1), the coefficient, a, needs to be specified. Where a, is a real number greater than zero and less than or equal to one: 0 < a ≦ 1. If the coefficient is set to one, then no filter is applied to the statistical result. Default is 1.0, which means that no filter is applied. SEED Defines an enumeration of recognized geometric pattern nicknames to be used in the creation of the resultant wafer map, which pertain to the semiconductor test paradigm. This is the pattern that will be used if a wafer map should be created upon the exceeding the Lower Hold Limit or Upper Hold Limit. The overlaid geometric pattern placed onto the wafer under test is defined by the Pattern enumerations: Pattern {Center-Only, Donut, Edge-Only, Edge-To-Center, Half-Moon, Notch-Only, Single-Site, Notch-To-Center}. SITE SELECTION Defines how sites that intersect the overlaid Pattern are included in the final wafer map creation. Sites that intersect the overlaid geometric pattern can be selected either by (1) using a checkerboard pattern of available sites, or (2) using percentage of total sites randomly selected. The selection criteria of intersecting sites is defined by keywords Checkerboard or Percentage.

In still more embodiments, the following example defines Register 100 with α=3 IIR Filter coefficient with the potential to trigger the creation of an Edge-Only wafer map with 20 percent random selection attached to the register mean statistic.

-   register=100, Cell Poly 10 sq Res, C, ohms/sq, 0, 1000 -   mean=−1.0e30, +1.0e30, 200, 400, 3085, 0.3, Edge-Only, 20     Creation of the new map for the specific register statistic may be     done once per wafer run as a stop criteria.

FIGS. 7A-7I illustrate example software data structures and interactions that can be used with embodiments of the present invention. Thus, in addition to or in conjunction with the example machine architecture 600B, presented in FIG. 6B, a group of software data structures 700A-700H interact to logically implement various embodiments of the present invention, where wafer test maps are dynamically created during a testing session.

For example, FIG. 7A illustrates the dynamic instantiation of two areas of new map, and FIG. 7B illustrates how the example software objects 700A can be organized in a class diagram 700B to dynamically create wafer test maps during a wafer lot testing session. A limit for the number of Map objects is reached when all testable sites of wafer 300A have been tested. Repeating sites can slow production throughput. FIG. 7C illustrates visually locations of test sites in both areas of the dynamically created wafer test map 700C.

If a site object has already been tested but intersects the area of the seed pattern, then this site is excluded from the newly created map. Each instance of a map contains sites, which have not yet been tested by a previous map. To ensure no test sites are revisited, a NonCircularDirectedGraph object is used (FIG. 7B). Each site is added the NonCircularDirectedGraph.

Moreover, if NonCircularDirectedGraph:AddEdge method returns false, then this means the site has already been added to the graph, and this site is excluded from the map. The test plan formal grammar can permit specifying the maximum number of maps.

If no upper limit is specified, then eventually all test sites may be tested. The test plan grammar is checked to ensure no duplicate test sites exist for a map. Creating a map can occur of at the end of the actively selected map progression or the actively selected map progression can be interrupted.

In some embodiments, Sites that intersect the overlaid geometric shape can be selected either by (1) using a checkerboard pattern of available sites, or (2) using percentage of total sites randomly selected. FIG. 7C shows how one seed map is formed from two areas. Each area has N and M sites respectively.

FIG. 7A, an example object instantiation diagram, illustrates the use of 20 percent of seeded test sites containing 20 test sites from A1: Area object and 20 percent of seeded test sites containing 40 sites from A2: Area object, resulting in 4 chosen sites from A-1: Area and 8 chosen sites from A-2: Area respectively, where the entire testable site population has been predefined in the wafer test plan. For each testable site there exists a physical die coordinate with one or more sub-site coordinates. Finally, each sub-site coordinate is associated with an executable electrical test, which generates one or more measurements.

In one embodiment, the Seed Bank procures a random distribution of sites by delegating to the Random Site Selector Class (FIG. 7B). The frequencies of the site occurrences of all the values should not be exactly the same. To ensure adequate randomness amongst the newly formed subset of sites, a chi-square test can be applied.

Thus, where N is the total number of intersected sites found from using the pattern, i is the index referencing a site coordinate of the AREA:set, and r is a number of sites less than N. If chi-square is close to r, then the sites are randomly selected; if it is too far away, then the sites are not randomly selected. $\chi^{2} = \frac{{\sum 0} \leq i < {r\left( {f_{i} - {N/r}} \right)}^{2}}{N/r}$

FIG. 7D, an example of the class diagram, illustrates relationship of ISSS, ISSP, and IIR filters with fast statistics Lookup Table (LUT). LUT is used to implement statistical threshold and control rules. Additionally, Map Progenitor is triggered by statistics events from ISSPs to create new maps.

In FIG. 7E, each measurement acquired from the parametric test system is uniquely identified by a register number, which is encapsulated in the ISSS Class diagram 700E. The measured value is added to the ISSS Processor, which maintains a raw sample of previously measured values for that same register. Statistics specifications associated with the register are calculated, and each resultant statistic is evaluated against its upper or lower control limit.

One example embodiment can be explained with the following condition: if a control limit is exceeded, then a ThresholdExceeded event is fired and received by the Map Progenitor object. The Map Progenitor uses this event stimulus to create a new map. To minimize false out-of-control alarms, an Input Impulse Filter can be applied.

Continuing with the present example, as depicted in FIG. 7E, each Register has zero to many Statistics Specifications. Each Statistics Specification holds onto its most recently calculated value posted by the ISSP. Looking from the Measurement's perspective, a Register uniquely identifies each Measurement. For the look up table implementation, a Standard Template Library (STL) Map can be used. FIG. 7F illustrates an example class diagram for an ISSS 700F.

Typical inline research and development parametric test systems may acquire millions of measurements during the lot-run. Most production part types running on inline parametric test systems have fewer than 1000 registers. In contrast, typical research and development part types can have 10,000 or more registers.

Furthermore, in FIG. 7G, each kind of measurement is uniquely defined by a register. There is a dedicated In Situ Statistics Sensor (ISSS) and In Situ Statistics Processor (ISSP) pair allocated for each Register.

Each time a measurement is acquired from the parametric tester, concurrently, statistics get calculated, filtered, and evaluated with respect to control limits. To prevent excessive triggering, a separate Infinite Response Filter bank is instantiated for each ISSP.

FIG. 7H shows that the time spent updating the sub-site collection, which is mostly bound for graphic card processing, is concurrent with the task of calculating statistics. Only if an upper or lower statically controlled limit is exceeded does an event fire requesting the creation of a new map.

FIG. 71 illustrates an example of composite state diagram governing the CWE 101D of the present invention and is included only for purposes of illustration. During the SubSite Test Composite State, new map create request may be queued, which will result in a new map creation during Map Create Setup Composite State.

Conclusion

Embodiments of the present invention address devices and methods concerning the dynamic creation of wafer test maps based on previous test results and/or seed templates for predefined geometric patterns. In one embodiment, a new wafer map is created while testing a wafer based upon an existing map, and the new wafer map pattern strategy is based on the test data gathered during that test. The new map may be based on patterns that are already stored in the test device (e.g., seed templates).

Other embodiments of the present invention can include map creation based upon test data obtained while a wafer is under test in a wafer test lot. Still other embodiments are directed to various testing circumstances, including parametric testing and probe.

The detailed discussion and examples above demonstrate how dynamic wafer map patterns can be dynamically created and modified to improve wafer testing by emboding a semiconductor engineer's experience and analysis in seed templates, which can be dynamically processed during a lot test session. 

1. A dynamic wafer testing system, comprising: a data store of patterns associated with testing maps; and a test station controller that dynamically creates one or more of the testing maps associated with a number of the patterns that are detected on sites to be tested on a lot of wafers, and wherein the test station controller can process a number of the dynamically created one or more testing maps in parallel.
 2. The dynamic wafer testing system 1, wherein the wafer test station controller dynamically creates one or more of the testing maps based on test results associated with testing another one of the testing maps.
 3. The dynamic wafer testing system of claim 1, wherein the wafer test station controller dynamically creates one or more of the testing maps by overlaying a number of the patterns acquired from the data store onto the sites identified for testing on the lot of wafers.
 4. The dynamic wafer testing system of claim 1, wherein if one of the testing maps tests one of the sites for one of the wafers in the lot, then the remaining testing maps do not retest the previously tested site for any of the remaining wafers being tested in the lot.
 5. The dynamic wafer testing system of claim 1, wherein a number of registers to test the wafers are identified in a test plan, and the registers include active sensors, and a number of testing maps that are created are limited by a configurable allocated production time and the registers with active sensors.
 6. The dynamic wafer testing system of claim 1, wherein the sites are used to form a default testing map for the wafers in the lot.
 7. A data store implemented in a machine-accessible medium, the data store used for assembling test maps, wherein the test maps are processed by a machine, the data store comprising: parameters associated with wafer test plans, wherein a particular one of the parameters identifies a particular one of the wafer test plans; and seeds associated with geometric shapes identified on wafers, wherein the seeds are sensitive to and include previously identified failing site locations on the wafers and failing site locations' symptoms, wherein the data store is to be accessed to selectively acquire one or more of the wafer test plans and to selectively acquire one or more of the seeds for dynamically assembling and processing tests on the wafers.
 8. The data store of claim 7, wherein the parameters further include types of data and/or statistics to be collected when the wafer test plans are processed on the wafers.
 9. The data store of claim 8, wherein the types of the data and/or statistics collected are to be stored in a parameter data store by the machine that processes the tests.
 10. The data store of claim 7, wherein the wafer test plans identify sites on the wafers to test and to identify test operations to be performed as a number of the tests on the wafers.
 11. The data store of claim 7, wherein the seeds are associated with specific test registers of the machine.
 12. The data store of claim 7, wherein the seeds are associated with seed maps that include at least one of a Single-Site seed map, a Center-To-Edge seed map, an Edge-Only seed map, a Center-Only seed map, and a Notch-Only seed map.
 13. A data store implemented in a machine-accessible medium, the data store used for housing results associated with processing dynamically created wafer test maps, the data store comprising: wafer identifiers associated with wafers; test identifiers associated with tests; and results associated with select ones of the wafer identifiers and associated with select ones of the test identifiers in response to processing select ones of the tests on select ones of the wafers.
 14. The data store of claim 13, wherein data types collected in the results are pre-defined and acquired from a different data store in response to the test identifiers.
 15. The data store of claim 13 further comprising, statistics associated with select ones of the wafer identifiers and associated with select ones of the test identifiers in response to processing select ones of the tests on select ones of the wafers.
 16. The data store of claim 13, wherein the results are to be populated with appropriate ones of the test identifiers and the wafers by a controller that processes the tests by updating the data store.
 17. A data structure implemented in a machine-accessible medium, the data structure representing a dynamically created and populated wafer test map pattern, the locations of the wafer test map pattern are associated with a wafer and at those locations within the wafer a machine processes tests, the data structure comprising: a wafer die for a given wafer; and a pattern within the wafer die, wherein the pattern is to be dynamically defined overlaying one or more shape templates on top of available test sites for the wafer die, and wherein the pattern represents a geometric pattern of locations within the wafer die where tests are to be performed.
 18. The data structure of claim 17, wherein the pattern excludes a number of the locations that are associated with any previously processed tests which were processed against the wafer die using an initial test map.
 19. The data structure of claim 17, wherein the shape templates are to be selectively acquired by a controller from a data store before the controller dynamically generates and populates the data structure.
 20. The data structure of claim 17, wherein the shape templates are represented in a formal mathematical representation and are processed to generate different patterns that are overlaid on the available test sites.
 21. A data structure implemented in a machine-accessible medium, the data structure defines a shape template for use in dynamically creating a wafer test map pattern, the test map pattern used to process tests on a wafer at defined locations associated with the pattern, and the data structure comprising: coordinates to define a center of a wafer die; a first set of sites to include within the wafer die relative to the center; and a second set of sites to exclude within the wafer die relative to the center; wherein the first and second sets represents locations identified for testing and locations identified for no testing within the wafer die as defined by the data structure, and wherein the locations identified for testing produce a geometric pattern or shape.
 22. The data structure of claim 21, wherein the first set is represented in formal mathematical notation within the data structure that when processed produces the geometric pattern or the shape.
 23. The data structure of claim 22, wherein the formal mathematical notation is a definition of a function, and wherein the function is at least one of quadratic and non quadratic.
 24. The method of claim 21, wherein multiple instances of the data structure are indexed and housed in a data store.
 25. A system, comprising: a testing data store to house one or more testing maps and one or more shape templates; and a results data store to house results data produced by processing tests; wherein a controller is to dynamically access the testing data store to selectively acquire one of the testing maps and one of the shape templates, and wherein the controller is to dynamically create a dynamic testing pattern on a wafer by overlaying the selected shape template and the selected testing map on the wafer to acquire the testing pattern, and the controller is to dynamically process select ones of the tests on locations of the wafer that are included within the testing pattern.
 26. The system of claim 25, wherein the testing data store further includes types of data and types of statistics to represents the results data, which the controller updates to the results data store in response to processing the select ones of the tests.
 27. The system of claim 25, wherein the selected shape template represents pre-identified problem areas within the wafer that are know to exist from previous tests processed against the wafer.
 28. A system, comprising: a test map; a seed data structure; and a new test map, wherein the test map is to define available locations within a wafer die for testing, the seed data structure is to define pre-defined problems within the wafer die at select ones of the available locations, and wherein the new test map is to be dynamically created by overlaying the seed data structure and the test map on the wafer die and excluding a number of the available locations where tests have already been processed and including remaining locations associated with the seed data structure.
 29. The system of claim 28, wherein the seed data structure is represented in formal notation to generate a pattern, the pattern when overlaid on the wafer die identifies the select locations within the wafer die.
 30. The system of claim 28 further comprising, a results data store to house results of tests processed using the new test map. 